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The effect of point mutations in Escherichia coli H + -F O F 1 ATP synthase on the MgADP-inhibition of ATPase activity

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Biochimica et Biophysica Acta (BBA) - Bioenergetics 2018年 1859卷 e82-e82页

作者： Tatiana E. Shugaeva Anna S. Lapashina Boris A. Feniouk Faculty of Bioengineering and Bioinformatics Lomonosov Moscow State University Moscow Russia A.N. Belozersky Institute of Physico-Chemical Biology Lomonosov Moscow State University Moscow Russia

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Biochemical properties of Escherichia coli F O F 1 -ATP synthase with Leu249Gln substitution in beta subunit

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Biochimica et Biophysica Acta (BBA) - Bioenergetics 2018年 1859卷 e80-e80页

作者： Anna S. Lapashina Boris A. Feniouk Faculty of Bioengineering and Bioinformatics Lomonosov Moscow State University Moscow Russia A.N. Belozersky Institute of Physico-Chemical Biology Lomonosov Moscow State University Moscow Russia

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Bioinformatic analysis of prokaryotic F-type ATP synthase operons

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Biochimica et Biophysica Acta (BBA) - Bioenergetics 2018年 1859卷 e76-e77页

作者： Boris A. Feniouk Tatiana D. Kholina Daria V. Dibrova Faculty of Bioengineering and Bioinformatics Lomonosov Moscow State University Moscow Russia A.N. Belozersky Institute of Physico-Chemical Biology Lomonosov Moscow State University Moscow Russia

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The repertoire of mutational signatures in human cancer (vol 578, pg 94, 2020)

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NATURE 2023年第7948期614卷 E41-E41页

作者： Alexandrov, Ludmil B. Kim, Jaegil Haradhvala, Nicholas J. Huang, Mi Ni Ng, Alvin Wei Tian Wu, Yang Boot, Arnoud Covington, Kyle R. Gordenin, Dmitry A. Bergstrom, Erik N. Islam, S. M. Ashiqul Lopez-Bigas, Nuria Klimczak, Leszek J. McPherson, John R. Morganella, Sandro Sabarinathan, Radhakrishnan Wheeler, David A. Mustonen, Ville Getz, Gad Rozen, Steven G. Stratton, Michael R. Department of Cellular and Molecular Medicine Department of Bioengineering Moores Cancer Center University of California San Diego CA USA Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Department of Cellular and Molecular Medicine and Department of Bioengineering University of California San Diego La Jolla CA USA UC San Diego Moores Cancer Center San Diego CA USA University of California San Diego San Diego CA USA Broad Institute of MIT and Harvard Cambridge MA USA Center for Cancer Research Massachusetts General Hospital Boston MA USA Massachusetts General Hospital Boston MA USA Department of Pathology Massachusetts General Hospital Boston MA USA Harvard Medical School Boston MA USA Laboratory for Medical Science Mathematics RIKEN Center for Integrative Medical Sciences Yokohama Japan Computational Biology Program Ontario Institute for Cancer Research Toronto ON Canada Programme in Cancer & Stem Cell Biology Duke-NUS Medical School Singapore Singapore Centre for Computational Biology Duke-NUS Medical School Singapore Singapore Programme in Cancer and Stem Cell Biology Duke-NUS Medical School Singapore Singapore Programme in Cancer and Stem Cell Biology Centre for Computational Biology Duke-NUS Medical School Singapore Singapore SingHealth Duke-NUS Institute of Precision Medicine National Heart Centre Singapore Singapore Singapore Cancer Science Institute of Singapore National University of Singapore Singapore Singapore Institute of Molecular and Cell Biology Singapore Singapore Laboratory of Cancer Epigenome Division of Medical Science National Cancer Centre Singapore Singapore Singapore Duke-NUS Medical School Singapore Singapore Human Genome Sequencing Center Baylor College of Medicine Houston TX USA Dan L. Duncan Cancer Center Baylor College of Medicine Houston TX USA Department of Molecular and Human Genetics Baylor College of Medicine Houston TX USA Genome Integrity and Structural Biology Laboratory National Ins

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Genomic basis for RNA alterations in cancer (vol 578, pg 129, 2020)

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NATURE 2023年第7948期614卷 E37-E37页

作者： Calabrese, Claudia Davidson, Natalie R. Demircioglu, Deniz Fonseca, Nuno A. He, Yao Lehmann, Kjong-Van Liu, Fenglin Shiraishi, Yuichi Soulette, Cameron M. Urban, Lara Greger, Liliana Li, Siliang Liu, Dongbing Perry, Marc D. Xiang, Qian Zhang, Fan Zhang, Junjun Bailey, Peter Erkek, Serap Hoadley, Katherine A. Hou, Yong Huska, Matthew R. Kilpinen, Helena Korbel, Jan O. Marin, Maximillian G. Markowski, Julia Nandi, Tannistha Pan-Hammarstrom, Qiang Pedamallu, Chandra Sekhar Siebert, Reiner Stark, Stefan G. Su, Hong Tan, Patrick Waszak, Sebastian M. Yung, Christina Zhu, Shida Awadalla, Philip Creighton, Chad J. Meyerson, Matthew Ouellette, B. F. Francis Wu, Kui Yang, Huanming Brazma, Alvis Brooks, Angela N. Goke, Jonathan Ratsch, Gunnar Schwarz, Roland F. Stegle, Oliver Zhang, Zemin European Molecular Biology Laboratory European Bioinformatics Institute Hinxton UK European Molecular Biology Laboratory European Bioinformatics Institute (EMBL-EBI) Cambridge UK Genome Biology Unit European Molecular Biology Laboratory (EMBL) Heidelberg Germany CIBIO/InBIO - Research Center in Biodiversity and Genetic Resources Universidade do Porto Vairão Portugal Berlin Institute for Medical Systems Biology Max Delbruck Center for Molecular Medicine Berlin Germany German Cancer Consortium (DKTK) partner site Berlin Germany German Cancer Research Center (DKFZ) Heidelberg Germany Berlin Institute for Medical Systems Biology Max Delbrück Center for Molecular Medicine Berlin Germany German Cancer Consortium (DKTK) Partner site Berlin Berlin Germany European Molecular Biology Laboratory Genome Biology Unit Heidelberg Germany Division of Computational Genomics and Systems Genetics German Cancer Research Center (DKFZ) Heidelberg Germany ETH Zurich Zurich Switzerland Memorial Sloan Kettering Cancer Center New York NY USA Weill Cornell Medical College New York NY USA SIB Swiss Institute of Bioinformatics Lausanne Switzerland University Hospital Zurich Zurich Switzerland Computational Biology Center Memorial Sloan Kettering Cancer Center New York NY USA Department of Biology ETH Zurich Zürich Switzerland Department of Computer Science ETH Zurich Zurich Switzerland Korea University Seoul South Korea Computational and Systems Biology Program Memorial Sloan Kettering Cancer Center New York NY USA Department of Physiology and Biophysics Weill Cornell Medicine New York NY USA Institute for Computational Biomedicine Weill Cornell Medicine New York NY USA Controlled Department and Institution New York NY USA Englander Institute for Precision Medicine Weill Cornell Medicine New York NY USA National University of Singapore Singapore Singapore Genome Institute of Singapore Singapore Singapore Computational and Systems Biology Genome Institute of Singap

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Author Correction: Predicting standardized uptake value of brown adipose tissue from CT scans using convolutional neural networks

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Nature communications 2024年第1期15卷 10022页

作者： Ertunc Erdil Anton S Becker Moritz Schwyzer Borja Martinez-Tellez Jonatan R Ruiz Thomas Sartoretti H Alberto Vargas A Irene Burger Alin Chirindel Damian Wild Nicola Zamboni Bart Deplancke Vincent Gardeux Claudia Irene Maushart Matthias Johannes Betz Christian Wolfrum Ender Konukoglu Computer Vision Lab. ETH Zurich Zurich Switzerland. ertunc.erdil@vision.ee.ethz.ch. Computer Vision Lab. ETH Zurich Zurich Switzerland. Department of Radiology Memorial Sloan Kettering Cancer Center New York NY USA. Institute for Diagnostic and Interventional Radiology University Hospital Zurich Zurich Switzerland. Department of Radiology NYU Grossman School of Medicine New York NY USA. Department of Nursing Physiotherapy and Medicine and SPORT Research Group (CTS-1024) CERNEP Research Center University of Almería Almería Spain. CIBER de Fisiopatología de la Obesidad y Nutrición (CIBEROBN) Instituto de Salud Carlos III Granada Spain. Department of Medicine Division of Endocrinology and Einthoven Laboratory for Experimental Vascular Medicine Leiden University Medical Center Leiden The Netherlands. Department of Physical Education and Sports Faculty of Sports Science Sport and Health University Research Institute (iMUDS) University of Granada 18071 Granada Spain. Instituto de Investigación Biosanitaria Ibs.Granada Granada Spain. Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y Nutrición (CIBERobn) Instituto de Salud Carlos III Madrid Spain. Department of Nuclear Medicine University Zurich Hospital Zurich Switzerland. University of Zurich Zurich Switzerland. Department of Radiology and Nuclear Medicine University Hospital of Basel Basel Switzerland. Swiss Multi-Omics Center ETH Zürich Zürich Switzerland. Laboratory of Systems Biology and Genetics Institute of Bioengineering School of Life Sciences Ecole Polytechnique Fédérale de Lausanne (EPFL) 1015 Lausanne Switzerland. Swiss Institute of Bioinformatics 1015 Lausanne Switzerland. Department of Endocrinology Diabetes and Metabolism University Hospital Basel and University of Basel Basel Switzerland. Department of Health Sciences and Technology ETH Zurich Zurich Switzerland. The LOOP Zürich - Medical Research Center Zürich Switzerland.

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The evolutionary history of 2,658 cancers (vol 578, pg 122, 2020)

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NATURE 2023年第7948期614卷 E42-E42页

作者： Gerstung, Moritz Jolly, Clemency Leshchiner, Ignaty Dentro, Stefan C. Gonzalez, Santiago Rosebrock, Daniel Mitchell, Thomas J. Rubanova, Yulia Anur, Pavana Yu, Kaixian Tarabichi, Maxime Deshwar, Amit Wintersinger, Jeff Kleinheinz, Kortine Vazquez-Garcia, Ignacio Haase, Kerstin Jerman, Lara Sengupta, Subhajit Macintyre, Geoff Malikic, Salem Donmez, Nilgun Livitz, Dimitri G. Cmero, Marek Demeulemeester, Jonas Schumacher, Steven Fan, Yu Yao, Xiaotong Lee, Juhee Schlesner, Matthias Boutros, Paul C. Bowtell, David D. Zhu, Hongtu Getz, Gad Imielinski, Marcin Beroukhim, Rameen Sahinalp, S. Cenk Ji, Yuan Peifer, Martin Markowetz, Florian Mustonen, Ville Yuan, Ke Wang, Wenyi Morris, Quaid D. Spellman, Paul T. Wedge, David C. Van Loo, Peter European Molecular Biology Laboratory European Bioinformatics Institute (EMBL-EBI) Cambridge UK European Molecular Biology Laboratory Genome Biology Unit Heidelberg Germany Wellcome Sanger Institute Cambridge UK Genome Biology Unit European Molecular Biology Laboratory (EMBL) Heidelberg Germany University of Ljubljana Ljubljana Slovenia The Francis Crick Institute London UK Big Data Institute University of Oxford Oxford UK Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Big Data Institute Li Ka Shing Centre University of Oxford Oxford UK University of Cambridge Cambridge UK Cambridge University Hospitals NHS Foundation Trust Cambridge UK Department of Applied Mathematics and Theoretical Physics Centre for Mathematical Sciences University of Cambridge Cambridge UK Department of Epidemiology and Biostatistics Memorial Sloan Kettering Cancer Center New York NY USA Department of Statistics Columbia University New York NY USA Department of Haematology University of Cambridge Cambridge UK University of Leuven Leuven Belgium Broad Institute of MIT and Harvard Cambridge MA USA Center for Cancer Research Massachusetts General Hospital Charlestown MA USA Department of Pathology Massachusetts General Hospital Boston MA USA Harvard Medical School Boston MA USA Center for Cancer Research Massachusetts General Hospital Boston MA USA Dana-Farber Cancer Institute Boston MA USA Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA Department of Cancer Biology Dana-Farber Cancer Institute Boston MA USA Oxford NIHR Biomedical Research Centre Oxford UK Oxford NIHR Biomedical Research Centre University of Oxford Oxford UK University of Toronto Toronto Ontario Canada Vector Institute Toronto Ontario Canada Vector Institute Toronto ON Canada Department of Computer Science University of Toronto Toronto ON Canada Ontario Institute for Cancer Research Toronto Ontario Canada University of California Los Angeles

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A thermodynamic framework for modelling membrane transporters

arXiv

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arXiv 2018年

作者： Pan, Michael Gawthrop, Peter J. Tran, Kenneth Cursons, Joseph Crampin, Edmund J. Systems Biology Laboratory School of Mathematics and Statistics Department of Biomedical Engineering Melbourne School of Engineering University of Melbourne ParkvilleVIC3010 Australia Auckland Bioengineering Institute University of Auckland Bioinformatics Division Walter and Eliza Hall Institute of Medical Research ParkvilleVIC3052 Australia Department of Medical Biology School of Medicine University of Melbourne ParkvilleVIC3010 Australia School of Medicine Faculty of Medicine Dentistry and Health Sciences University of Melbourne ParkvilleVIC3010 Australia ARC Centre of Excellence in Convergent Bio-Nano Science and Technology Melbourne School of Engineering University of Melbourne ParkvilleVIC3010 Australia

Membrane transporters contribute to the regulation of the internal environment of cells by translocating substrates across cell membranes. Like all physical systems, the behaviour of membrane transporters is constrained by the laws of thermodynamics. However, many mathematical models of transporters, especially those incorporated into whole-cell models, are not thermodynamically consistent, leading to unrealistic behaviour. In this paper we use a physics-based modelling framework, in which the transfer of energy is explicitly accounted for, to develop thermodynamically consistent models of transporters. We then apply this methodology to model two specific transporters: the cardiac sarcoplasmic/endoplasmic Ca2+ATPase (SERCA) and the cardiac Na+/K+ATPase. Copyright © 2018, The Authors. All rights reserved.

关键词： Energy transfer

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Comparative Study of the Silver Nano-/Microstructures Deposited from Aerosol and Fog

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Advances in Nanoparticles 2017年第3期6卷 128-139页

作者： A. V. Zheltova E. V. Maslyonkova Yu. G. Biryukov P. R. Kasanskii S. M. Ryndya A. S. Smolyanskii Faculty of Bioengineering and Bioinformatics Lomonosov Moscow State University Moscow Russia Pirogov Russian National Research Medical University Moscow Russia Branch of JSC “Karpov Institute of Physical Chemistry” Moscow Russia JSC “Systems of Microscopy and Analysis” Moscow Russia National Research Nuclear University “MePhi” Moscow Russia Mendeleev University of Chemical Technology Moscow Russia

A comparative study of the structure and fractal properties of arrays of the silver nano-/micro-particles deposited on the silicon substrate both from the aerosol and fog showed that the form of the silver individual particles and nano-/microstructures greatly depends on the deposition conditions. By passing an aerosol through isopropyl alcohol, the formation of fractal aggregates of the silver nano-/micro-particles both in the air and in alcohol was observed. Deposition of the silver nano-/micro-particles in the atmosphere of the saturated isopropyl alcohol vapours led to formation of fog. Microdroplets of the silver colloidal solution were deposited on the substrate. The further evaporation of alcohol created the silver nano/microstructures in the form of annular layers. It was found that the concerned annular layers contained silver particles of the same shape in the form of a Crescent (or Janus-nano-/microparticles). The nature of discovered effects is discussed.

关键词： Aerosol Fog Silver Deposition Janus-Nanoparticle Fractal Aggregate

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Where are the limits of the centrosome?

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BioArchitecture 2016年第3期6卷 47-52页

作者： Alieva, Irina B. Uzbekov, Rustem E. A. N. Belozersky Institute of Physico-Chemical Biology Moscow State University Moscow Russian Federation Laboratory of Cell Biology and Electron Microscopy Faculty of Medicine François Rabelais University Tours France Faculty of Bioengineering and Bioinformatics Moscow State University Moscow Russian Federation

ABSTRACT: The centrosome is a key component of the cell is involved in the processes of cell division, cell motility, intracellular transport, organization of the microtubules (MT) network and the production of cilia and flagella. The peculiarity of this organelle is that its boundaries are not clearly defined, the centrioles at the center of the centrosome are surrounded by electron dense pericentriolar material, the size and protein composition of this centrosome component experiences significant transformation during the cell cycle. It has been shown in this study that within the centrosome different proteins occupy different areas corresponding to: MT nucleation region (defined as gamma-tubulin-stained area), regulatory region (defined as kinase pEg2-stained area) and motor proteins region (kinesin-like motor XlEg5-stained area). The boundary of pEg2 is near 1.3 times greater while XlEg5 is 3.0 times greater than that of gamma-tubulin. Thus, the size of the centrosome, determined according to the structural electron microscopy (EM) analysis (about 1 µm) corresponds to the regulatory proteins area, but the actual functional centrosome size defined at the motor proteins region, is more than twice the size. © 2016 Taylor & Francis Group, LLC.

关键词： centriole centrosome microtubules mitosis pericentriolar material prophase

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